Revolutionizing ORR catalyst design through computational methodologies and materials informatics

Abstract

Computational approaches, such as density functional theory (DFT) in conjunction with descriptor-based analysis and computational hydrogen electrode, have enabled exploring the intricate interactions between catalyst surfaces and oxygen species allowing for the rational design of materials with optimized electronic structure and reactivity for oxygen reduction reaction (ORR). The identification of active sites and the tuning of catalyst compositions at the atomic scale have been facilitated by computational simulations, accelerating the discovery of promising ORR catalysts. In this contribution, the insights provided by the computational analysis to understand the fundamental reasons behind inherent ORR overpotentials in the experimental reported catalysts are discussed. Various strategies to overcome the limitations in ORR catalysis using computational design are discussed. Several alternative earth-abundant and cost-effective materials suggested by computational guidance to replace platinum-based catalysts are reviewed. The accuracy of DFT and the role of solvent and electrolyte pH are outlined based on the understanding provided by the computational insight. Finally, an overview of recent achievements in employing materials informatics to accelerate catalyst material discovery for ORR is provided. These computational advancements hold great promise for the development of efficient and cost-effective ORR catalysts, bringing us closer to realizing the full potential of fuel cells as efficient electrochemical energy conversion technologies.